Robust Implementation of Coplanarity-Based Method for Camera Pose Estimation

In this paper, we consider a method for estimating camera motion parameters from images acquired from this camera, which is based on the use of vector coplanarity estimation. It has been previously shown that the proposed approach can be effectively applied to three-dimensional scenes invariant to t...

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Bibliographic Details
Published in:Optical memory & neural networks 2024-12, Vol.33 (Suppl 2), p.S261-S269
Main Author: Goshin, Ye. V.
Format: Article
Language:English
Subjects:
Complexity
Computer Science
Information Storage and Retrieval
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Summary:In this paper, we consider a method for estimating camera motion parameters from images acquired from this camera, which is based on the use of vector coplanarity estimation. It has been previously shown that the proposed approach can be effectively applied to three-dimensional scenes invariant to their depth. However, due to the criterion used, it is difficult to utilize the RANSAC method to ensure the robustness of the developed method. In this paper, an approach based on the minimum covariance determinant estimation method is proposed. The proposed approach allows us to select the most consistent observations and make an estimation based on these observations. An experimental study of the proposed approach on synthetic data has been carried out. It is shown that the proposed algorithm can provide a significant increase in the reliability of motion parameters determination even in conditions of a small number of corresponding points
ISSN:1060-992X
1934-7898
DOI:10.3103/S1060992X24700541